Noninvasive ultrasound measurement of shear rate in leg bypass grafts.

Shear has been implicated in the etiology of atherosclerosis, thrombosis and graft stenosis. We measured shear rate noninvasively in infrainguinal bypasses. Velocity profiles were recorded from 35 femoropopliteal and 40 tibial grafts. Flow rate (Q), systolic shear rate (SSR), diameter, and bluntness factor (BF) were measured at midgraft using ultrasound (US). Mean shear rate (MSR) was calculated from flow and diameter. SSR, 671 +/- 260 (SD) vs. 659 +/- 304 s(-1) (p = 0.85), and MSR, 168 +/- 84 vs. 193 +/- 110 s(-1) (p = 0.26), were similar for popliteal and tibial bypasses, but differences in Q, 126 +/- 57 vs. 104 +/- 38 mL/min, were borderline significant (p = 0.058). Popliteal grafts had larger diameters, 5.2 +/- 1.1 mm vs. 4.7 +/- 0.8 mm (p = 0.048), and BF, 3.4 +/- 0.9 vs. 2.8 +/- 0.7 (p = 0.0014). Shear rates were obtained noninvasively in humans. Larger diameters in popliteal vs. tibial bypasses did not result in lower shear rates and were compensated for by larger bluntness factors. Velocity profile bluntness cannot be ignored in shear rate analysis.

Enhancement of Xe-133 ventilation lung scan image acquired after Tc-99m perfusion scan.

In nuclear medicine, the match and mismatch between the images of lung perfusion and ventilation provide an important criterion to diagnose pulmonary embolism. Usually, for imaging clarity, the ventilation scan using 133Xe is performed before the perfusion scan using 99mTc. But the inverse order is preferred clinically, since (i) if the perfusion image is normal, there is no need to do the ventilation scan, and (ii) if the perfusion image is abnormal, the ventilation image can be obtained by focusing on the perfusion abnormalities. However, the quality of the ventilation image is reduced if the ventilation scan is performed after the perfusion scan, because the 140 keV photons emitted from 99mTc will scatter into the acquisition window of 133Xe (81 keV). The purpose of this study is to apply image processing techniques to reduce the scattering effect of 99mTc to get a better 133Xe ventilation image. First, an image sequence in the preferred inverse order is simulated using the images acquired in the normal order. Image processing techniques are used to find an optimized way to reduce the scattering background in the ventilation image. Second, a real image sequence is acquired in the inverse order. An improved ventilation image is then obtained by applying image processing techniques to this image sequence.

Computer analysis of human depth EEG in different sleep stages.

This study compares delta (< 4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (12-20 Hz) band EEG signals during wakefulness, rapid-eye-movement (REM) sleep, and stage 1 and stage 2 non-REM sleep recorded from both surface and depth electrodes in patients with drug-resistant partial seizures. Computer analysis utilizing Fast Fourier Transforms (FFT) was performed with the Neurovision software developed for this purpose. Mean amplitudes were calculated for each of the frequency bands. Preliminary analysis was performed with emphasis on the presence and characteristics of theta activity in the hippocampus of the brain. Results demonstrate theta wave activity in the hippocampus with an increase of theta activity in REM sleep as compared to non-REM sleep (stages 1 and 2).

SD filtering for enhancement of a nuclear medicine image sequence.

This paper explores the use of an image sequence processing algorithm, called the simultaneous diagonalization (SD) filter, which can be effectively applied to long noisy image sequences. This filter was developed to filter a spatially invariant image sequence to form one new image in which a desired feature is enhanced and one or more undesired features (and noise) are suppressed in the filtered image. This filtering technique, applied to a long noisy image sequence, can be used to achieve significant data compression for image storage and provide surprisingly good enhanced image reconstructions. For this investigation, SD filtering is applied to a temporal image sequence, a renogram, with compression of a very noisy 180-image sequence to a 4-image set. The renogram, a nuclear medicine technique, was chosen due to its low signal-to-noise ratio over a long image sequence. Before the application of the SD filter, classical image processing techniques, median and averaging filtering, are used as a preliminary method to reduce the image sequence noise content. Compared to any of the images in the original image sequence, the reconstructed images are remarkably good. The SD filter with prefiltering, thus, can collect information distributed over a 180-image temporal sequence with low signal-to-noise ratio.

Spatially invariant image sequences.

The authors define linearly additive spatially invariant image sequences and present an explicit mathematical model for describing them. In such a sequence, all objects are positionally invariant in each image of the sequence but have varying gray-scale contributions to the successive images of the sequence. The various components (features or processes) of the scene or object contribute additively to each image of the sequence, but each component has a characteristic variation (signature) from image to image due to the variation of the function, parameter or spectral band over the sequence. Objects with different spectral characteristics will have different image sequence signatures which can be used to distinguish them. Also presented are the general formulation, derivation, and explicit expression for the linear filter, called the simultaneous diagonalization (SD) filter, that calculates a single new image from the sequence such that a desired process is emphasized and any number of undesired processes is suppressed in the filtered image.

Computer model for simulation of first transit cardiac radionuclide curves--I.

A discrete-time, lumped-parameter mathematical model of the human cardiopulmonary circulation as it appears during a first-transit radionuclide study is developed. Eleven compartments, four delays, and 26 transfer paths are modeled, including the entire circulation from an input compartment before the vena cava to an output compartment after the aorta. The 26 transfer paths include forward and reverse flow through the heart valves, backflow from the atria into the veins, and five types of shunts. A method of modeling continuously-variable delay segments with only discrete-time sample points is devised to allow more versatility in specifying delays. The model simulates discrete time-activity curves for the various compartments of the cardiopulmonary system. The curves are obtained for end-systole and end-diastole. Simulation of curves indicative of a normal heart and several heart defects is presented. The use of this model for computer analysis of first-transit cardio-radionuclide curves is discussed.

Optimal fitting of computer model simulations to first transit cardiac radionuclide curves--II.

A discrete-time, lumped-parameter mathematical model of the human cardiopulmonary circulation as it appears during a first-transit radionuclide study has been described. An optimal fitting process is used to match curves obtained from the model to curves obtained from first transit studies in order to estimate the parameters of the subject's heart. The development of the optimization technique is described in this paper. The results of testing the effects of overlapping compartments and errors in delay estimates are presented. A parameter determination analysis is performed by applying the optimization algorithm to simulated data. This analysis technique provides a method of estimating many parameters of heart function using a single, simple, rapid procedure. Results of clinical studies will be presented subsequently.